Kolmogorov-Smirnov test for exponentiality

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Description

Performs Kolmogorov-Smirnov test for the composite hypothesis of exponentiality, see e.g. Henze and Meintanis (2005, Sec. 2.1).

Usage

1
ks.exp.test(x, nrepl=2000)

Arguments

x

a numeric vector of data values.

nrepl

the number of replications in Monte Carlo simulation.

Details

The Kolmogorov-Smirnov test for exponentiality is based on the following statistic:

KS_n =\sup_{x≥q0}|F_n(x)-(1-\exp(-x))|,

where F_n is the empirical distribution function of the scaled data Y_j=X_j/\overline{X}. The p-value is computed by Monte Carlo simulation.

Value

A list with class "htest" containing the following components:

statistic

the value of the Kolmogorov-Smirnov statistic.

p.value

the p-value for the test.

method

the character string "Kolmogorov-Smirnov test for exponentiality".

data.name

a character string giving the name(s) of the data.

Author(s)

Ruslan Pusev and Maxim Yakovlev

References

Henze, N. and Meintanis, S.G. (2005): Recent and classical tests for exponentiality: a partial review with comparisons. — Metrika, vol. 61, pp. 29–45.

Examples

1
2
ks.exp.test(rexp(100))
ks.exp.test(runif(100, min = 50, max = 100))